The number of partners and sub-partners recording narrative data

Not all partners (and sub-partners) enter narrative records.

The number cantons and provinces recording narrative data

The table is alphabetically ordered.

Treemap plot showing canton and province reporting frequencies.

Word count

One issue with the nature of the questions is that they are only unique in a form. These questions can be distributed across multiple forms. The questions sharing the same name will have different meanings. For instance, the question “Cualitativo” from the form “Salud” should imply different thing than the question “Cualitativo” from the form “Protección_VBG”.

In order to solve this kind of problem:

• We can combine question with the form and also its folder label. There we can achieve a unique name for each question.

• Another thing to resolve this would be doing analysis to move the analysis up to form level. In this file, we did both, therefore the analysis shown as below:

Count of responses per topic/question:

It’s also a good practice to see the number of questions. For example, one question has two responses, therefore they’re short. Therefore, jittered points are added to give a glance about the number of observations in the same plot.

Figure: Box plot form topics and response word counts based on the raw data

In the plot above, the outliers are shown in orange color. Outliers are the points placed outside the whiskers, which is the long line, of the boxplot[^1].

The response word count distribution per form topic categorized by partner name:

The response word count distribution per form topic categorized by canton name:

A caveat: Reducing multiple values down to a single value should be avoided in the early stages of the analysis because reducing hides a lot e.g. a bar chart showing average the word count per partner. Some partners may write longer than others, because:

1. They actually write longer than other partners.

2. The questions they answered require short answers.

The “Description” field

Some questions have the description field giving extra details about the questions.

Do some questions with the extra description field have better response quality than the questions which do not have it?

Looking at the table containing form name, question, description and so on:

We see in the plot below that the response word counts per form and colored if a response has a description field or not. Having a description field or not is calculated as that a description field has a minimum one word.

The responses with the longest word counts are the ones with description. Nevertheless, it is not so easy to see a clear trend that there’s a correlation between response word count and description fields. Interestingly, the questions in the form F15, which is Protección_VBG, has no description fields at all.

We look below the description word count and compare with the response word count (and remove the categorical field displaying if the question of response has a description field).

TODO ANOVA

Correlation

TODO

The regression line

We can look at multiple continuous variables in our data.

• word count of response field: the dependent variable.

• word count of question field: an independent variable.

• word count of description field: an independent variable.

Scatter plots help understand the characteristics of those variables. However, we miss a general understanding that is the trend line.

The gray area around the lines shows the confidence band at the 0.95 level. Although there’s a straight slope in the linear regression line, we cannot say that the trend line is robust because the confidence band representing the uncertainty in the estimate is wide.

Logistic regression

TODO